Individual disk capacity has been growing at roughly seventy percent (70%) per year over the last decade. Moore's law accurately predicted the tremendous gains in central processing unit (CPU) power that has occurred over the years. Wired and wireless technologies have provided tremendous connectivity and bandwidth. Presuming current trends continue, within several years the average laptop computer will possess roughly one terabyte (TB) of storage and contain millions of files, and 500 gigabyte (GB) drives will become commonplace.
Consumers use their computers primarily for communication and organizing personal information, whether it is traditional personal information manager (PIM) style data or media such as digital music or photographs. The amount of digital content, and the ability to store the raw bytes, has increased tremendously; however the methods available to consumers for organizing and unifying this data has not kept pace. Knowledge workers spend enormous amounts of time managing and sharing information, and some studies estimate that knowledge workers spend 15-25% of their time on non-productive information related activities. Other studies estimate that a typical knowledge worker spends about 2.5 hours per day searching for information.
Developers and information technology (IT) departments invest significant amounts of time and money in building their own data stores for common storage abstractions to represent such things as people, places, times, and events. Not only does this result in duplicated work, but it also creates islands of common data with no mechanisms for common searching or sharing of that data. Just consider how many address books can exist today on a computer running the Microsoft Windows operating system. Many applications, such as e-mail clients and personal finance programs, keep individual address books, and there is little sharing among applications of the address book data that each such program individually maintains. Consequently, a finance program (like Microsoft Money) does not share addresses for payees with the addresses maintained in an email contact folder (like the one in Microsoft Outlook). Indeed, many users have multiple devices and logically should synchronize their personal data amongst themselves and across a wide variety of additional sources, including cell phones to commercial services such as MSN and AOL; nevertheless, collaboration of shared documents is largely achieved by attaching documents to e-mail messages-that is, manually and inefficiently.
One reason for this lack of collaboration is that traditional approaches to the organization of information in computer systems have centered on the use of file-folder-and-directory-based systems (“file systems”) to organize pluralities of files into directory hierarchies of folders based on an abstraction of the physical organization of the storage medium used to store the files. The Multics operating system, developed during the 1960s, can be credited with pioneering the use of the files, folders, and directories to manage storable units of data at the operating system level. Specifically, Multics used symbolic addresses within a hierarchy of files (thereby introducing the idea of a file path) where physical addresses of the files were not transparent to the user (applications and end-users). This file system was entirely unconcerned with the file format of any individual file, and the relationships amongst and between files was deemed irrelevant at the operating system level (that is, other than the location of the file within the hierarchy). Since the advent of Multics, storable data has been organized into files, folders, and directories at the operating system level. These files generally include the file hierarchy itself (the “directory”) embodied in a special file maintained by the file system. This directory, in turn, maintains a list of entries corresponding to all of the other files in the directory and the nodal location of such files in the hierarchy (herein referred to as the folders). Such has been the state of the art for approximately forty years.
However, while providing a reasonable representation of information residing in the computer's physical storage system, a file system is nevertheless an abstraction of that physical storage system, and therefore utilization of the files requires a level of indirection (interpretation) between what the user manipulates (units having context, features, and relationships to other units) and what the operating system provides (files, folders, and directories). Consequently, users (applications and/or end-users) have no choice but to force units of information into a file system structure even when doing so is inefficient, inconsistent, or otherwise undesirable. Moreover, existing file systems know little about the structure of data stored in individual files and, because of this, most of the information remains locked up in files that may only be accessed (and comprehensible) to the applications that wrote them. Consequently, this lack of schematic description of information, and mechanisms for managing information, leads to the creation of silos of data with little data sharing among the individual silos. For example, many personal computer (PC) users have more than five distinct stores that contain information about the people they interact with on some level—for example, Outlook Contacts, online account addressees, Windows Address Book, Quicken Payees, and instant messaging (IM) buddy lists—because organizing files presents a significant challenge to these PC users. Because most existing file systems utilize a nested folder metaphor for organizing files and folders, as the number of files increases the effort necessary to maintain an organization scheme that is flexible and efficient becomes quite daunting. In such situations, it would be very useful to have multiple classifications of a single file; however, using hard or soft links in existing file systems is cumbersome and difficult to maintain.
Several unsuccessful attempts to address the shortcomings of file systems have been made in the past. Some of these previous attempts have involved the use of content addressable memory to provide a mechanism whereby data could be accessed by content rather than by physical address. However, these efforts have proven unsuccessful because, while content addressable memory has proven useful for small-scale use by devices such as caches and memory management units, large-scale use for devices such as physical storage media has not yet been possible for a variety of reasons, and thus such a solution simply does not exist. Other attempts using object-oriented database (OODB) systems have been made, but these attempts, while featuring strong database characteristics and good non-file representations, were not effective in handling file representations and could not replicate the speed, efficiency, and simplicity of the file and folder based hierarchical structure at the hardware/software interface system level. Other efforts, such as those that attempted to use SmallTalk (and other derivatives), proved to be quite effective at handling file and non-file representations but lacked database features necessary to efficiently organize and utilize the relationships that exist between the various data files, and thus the overall efficiency of such systems was unacceptable. Yet other attempts to use BeOS (and other such operating systems research) proved to be inadequate at handling non-file representations—the same core shortcoming of traditional file systems—despite being able to adequately represent files while providing some necessary database features.
Database technology is another area of the art in which similar challenges exits. For example, while the relational database model has been a great commercial success, in truth independent software vendors (ISV) generally exercise a small portion of the functionality available in relational database software products (such as Microsoft SQL Server). Instead, most of an application's interaction with such a product is in the form of simple “gets” and “puts”. While there are a number of readily apparent reasons for this—such as being platform or database agnostic—one key reason that often goes unnoticed is that the database does not necessarily provide the exact abstractions that a major business application vendor really needs. For example, while the real world has the notion of “items”, such as “customers” or “orders” (along with an order's embedded “line items” as items in and of themselves), relational databases only talk in terms of tables and rows. Consequently, while the application may desire to have aspects of consistency, locking, security, and/or triggers at the item level (to name a few), generally databases provide these features only at the table/row level. While this may work fine if each item gets mapped to a single row in some table in the database, in the case of an order with multiple line items there may be reasons why an item actually gets mapped to multiple tables and, when that is the case, the simple relational database system does not quite provide the right abstractions. Consequently, an application must build logic on top of the database to provide these basic abstractions. In other words, the basic relational model does not provide a sufficient platform for storage of data on which higher-level applications can easily be developed because the basic relational model requires a level of indirection between the application and the storage system—where the semantic structure of the data might only be visible in the application in certain instances. While some database vendors are building higher-level functionality into their products—such as providing object relational capabilities, new organizational models, and the like—none have yet to provide the kind of comprehensive solution needed, where a truly comprehensive solution is one which provides both useful data model abstractions (such as “Items,” “Extensions,” “Relationships,” and so on) for useful domain abstractions (such as “Persons,” “Locations,” “Events,” etc.).
In view of the foregoing deficiencies in existing data storage and database technologies, there is a need for a new storage platform that provides an improved ability to organize, search, and share all types of data in a computer system—a storage platform that extends and broadens the data platform beyond existing file systems and database systems, and that is designed to be the store for all types of data. The related inventions, incorporated by reference earlier herein, satisfies this need.
However, the storage of images (photos, digital images, etc.) is not standardized and is not generalized across platforms and applications. While applications can include APIs tailored to a particular image format (e.g., JPEG), developers of such applications must be aware of the format, include tailored application programming interfaces (APIs), and perform any conversions necessary to interoperate with said format. What is missing in the art is a common schema (or set of schemas) for all image objects in a computer system, and the present invention, in conjunction with the related inventions incorporated by reference earlier herein, satisfies this specific need.